Simulating assignment inference. To simulate the outcome of assignment inference, it is necessary to (a) determine which assignment is optimal according to an assignment problem [1]} and (b) estimate the probability of inferring any one assignment over all alternative assignment(s), which is given by semantic distance. The combination of these two pieces of information indicates which colors observers will map to which concepts in assignment inference, and the probability that they will infer that assignment. This method is effective for predicting how people map colors to concepts for visualizations of categorical information (e.g., recycling bin signage [2]}, bar charts [3]}, [4]}), although earlier work did not yet refer to “semantic distance” by name [2]}. This approach may also extend to inferences about properties of food and beverage products based on coloring in package design [6]}.
